GATA3 and MDM2 are synthetic lethal in estrogen receptor-positive breast cancers

Bianco, Gaia; Coto‐Llerena, Mairene; Gallon, John; Taha‐Mehlitz, Stephanie; Kancherla, Venkatesh; Konantz, Martina; Srivatsa, Sumana; Montazeri, Hesam; Panebianco, Federica; Menna, Marta De; Paradiso, Viola; Ercan, Caner; Dahmani, Ahmed; Montaudon, Élodie; Beerenwinkel, Niko; Julio, Marianna Kruithof-de; Terracciano, Luigi; Lengerke, Claudia; Bidard, François‐Clément; Jeselsohn, Rinath; Marangoni, Elisabetta; Ng, Charlotte K.Y.; Piscuoglio, Salvatore

doi:10.1101/2020.05.18.101998

Cited by 4 publications

(3 citation statements)

References 83 publications

(102 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…4 , 5 ), and GATA3-MDM2 in breast cancer. In a recent study by Bianco et al 60 , GATA3 and MDM2 were found to be synthetic lethal in estrogen receptor-positive breast cancers. Thus, through parallel analysis and integration of the two datasets, SLIdR reports robust and complementary SL pairs.…”

Section: Resultsmentioning

confidence: 91%

Discovery of synthetic lethal interactions from large-scale pan-cancer perturbation screens

et al. 2022

Self Cite

View full text Add to dashboard Cite

The development of cancer therapies is limited by the availability of suitable drug targets. Potential candidate drug targets can be identified based on the concept of synthetic lethality (SL), which refers to pairs of genes for which an aberration in either gene alone is non-lethal, but co-occurrence of the aberrations is lethal to the cell. Here, we present SLIdR (Synthetic Lethal Identification in R), a statistical framework for identifying SL pairs from large-scale perturbation screens. SLIdR successfully predicts SL pairs even with small sample sizes while minimizing the number of false positive targets. We apply SLIdR to Project DRIVE data and find both established and potential pan-cancer and cancer type-specific SL pairs consistent with findings from literature and drug response screening data. We experimentally validate two predicted SL interactions (ARID1A-TEAD1 and AXIN1-URI1) in hepatocellular carcinoma, thus corroborating the ability of SLIdR to identify potential drug targets.

show abstract

Section: Resultsmentioning

confidence: 91%

Discovery of synthetic lethal interactions from large-scale pan-cancer perturbation screens

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…Besides our classifier, a nonluminal disease score [ 64 ] based on percentage of ER , PR , and MKI67 tumor cells was easy, fast, and with the potential to be widely implemented to identify nonluminal disease within ER + /HER2 − breast cancer when gene expression data are not available. A recent study [ 65 ] presented GATA3 and MDM2 were synthetically lethal in ER + breast cancer, where MDM2 was a novel therapeutic target in GATA3 ‐deficient subsets. Those results support the usefulness of our two‐gene panel, in identifying a subgroup of ER + HER2 − breast cancer with bad prognosis as candidates for novel individualized therapy.…”

Section: Discussionmentioning

confidence: 99%

Integrated multi‐omics profiling of high‐grade estrogen receptor‐positive, HER2‐negative breast cancer

Wang

Franch-Expósito

et al. 2021

Molecular Oncology

View full text Add to dashboard Cite

Estrogen-receptor-positive, and human epidermal growth factor receptor 2-negative (ER+HER2−) breast cancer accounts for ~60−70% of all cases of invasive breast carcinoma. High-grade ER+HER2− tumors respond poorly to endocrine therapy. In this study, we systematically analyzed clinical and multi-omics data to find potential strategies for personalized therapy of patients with high-grade ER+HER2− disease. Six different cohorts were analyzed, for which multi-omics data were available. Grade III ER+HER2-cases harbored higher proportions of large tumor size (>5cm), lymph nodes metastasis, chemotherapy use and luminal B subtypes defined by PAM50, as compared with grade I/II tumors. DNA methylation (HM450) data and methylation specific PCR indicated that the cg18629132 locus in the MKI67 promoter was hypermethylated in grade I/II cases and normal tissue, but hypomethylated in grade III cases or triple negative breast cancer (TNBC), resulting in higher expression of MKI67. Mutations in ESR1 and TP53 were detected in post-endocrine−treatment metastatic samples at a higher rate than in treatment-naive tumors in grade III cases. We identified 42 and 20 focal copy number events in non-metastatic and metastatic high-grade ER+HER2− cases, respectively, with either MYC or MDM2 amplification representing an independent prognostic event in grade III cases. Transcriptional profiling within grade III tumors, highlighted ER signaling downregulation and upregulation of immune-related pathways in non-luminal-like tumors defined by PAM50. Recursive partitioning analysis (RPA) was employed to construct a decision tree of an endocrine-resistant subgroup (GATA3-negative and AGR-negative) of two genes that was validated by immunohistochemistry in a Chinese cohort. All together, these data suggest that grade III ER+HER2− tumors have distinct clinical and molecular characteristics compared with low-grade tumors, particularly in cases with non-luminal-like biology. Due to the dismal prognosis in this group, clinical trials are warranted to test the efficacy of potential novel therapies.

show abstract

“…23.529701 doi: bioRxiv preprint associations (n=286) represent increased dependency (i.e., lower dependency score) of a given gene with increased TFa and positive associations (n=239) represent increased dependency with decreased TFa (Fig 1b). Among the predicted associations, we identified seven self-dependent TFs i.e., increased dependency of a TF was associated with its own increased activity (e.g., NRF2/NFE2L2, JUN), previously reported synthetic lethal associations (e.g., GATA3-MDM2 33 ) and previously unknown associations (e.g., TEAD1-RAC1, KLF5-STX4). We also observed TFa-target pairs where the associated dependency target gene is also a TF (e.g., TEAD1-FOSL1), suggesting that essentiality of a TF can be potentially predicted by the activity of associated TFs (Supp Table 2).…”

Section: Identification Of Pan-cancer Tf Activity-associated Gene Dep...mentioning

confidence: 90%

Genetic dependencies associated with transcription factor activities in human cancer cell lines

Thatikonda

Supper

Ravichandran

et al. 2023

Preprint

View full text Add to dashboard Cite

Transcription factors (TFs) are key components of the aberrant transcriptional programs in cancer cells. In this study, we used TF activity (TFa), inferred from the downstream regulons as a potential biomarker to identify associated genetic vulnerabilities in cancer cells. Our linear model framework, integrating TFa and genome-wide CRISPR knockout datasets identified 1,770 candidate TFa target pairs across different cancer types and assessed their survival impact in patient data. As a proof of concept, through inhibitor screens and genetic depletion assays in cell lines, we validated the dependency of cell lines on predicted targets linked to TEAD1, the most prominent TF from our analysis. Overall, these candidate pairs represent an attractive resource for early-stage targets and drug discovery programs in oncology.

show abstract

GATA3 and MDM2 are synthetic lethal in estrogen receptor-positive breast cancers

Cited by 4 publications

References 83 publications

Discovery of synthetic lethal interactions from large-scale pan-cancer perturbation screens

Discovery of synthetic lethal interactions from large-scale pan-cancer perturbation screens

Integrated multi‐omics profiling of high‐grade estrogen receptor‐positive, HER2‐negative breast cancer

Genetic dependencies associated with transcription factor activities in human cancer cell lines

Contact Info

Product

Resources

About